Andrew Y. Ng

45 papers · 2003–2024 · 13 conferences · across top CS/AI conferences

Achievements

+15 more ↓

🗺️ Taxonomy Completionist (30) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (10) 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird

🏃 Academic Marathon (21) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (10) 🏠 Conference Loyalist (21) 🌟 Keyword Trendsetter Combo (10) 🌱 Topic Pioneer 🏆 Keyword Champion (3) 🔬 Deep Specialist (10) 👥 Mega-Team (47) 🗃️ Keyword Collector (131) 🚀 Conference Pioneer 📈 Trend Setter ⚡ Prolific Year (7) 💎 Century Club (45) 🔥 Unstoppable (5)

Conferences

NIPS (21) MIDL (5) EMNLP (4) ACL (3) CONLL (2) JMLR (2) MLHC (2) AAAI (1) COLING (1) CVPR (1) ICLR (1) RSS (1) UAI (1)

Top co-authors

Christopher D. Manning (7) Pranav Rajpurkar (7) Richard Socher (6) Quoc V Le (4) Rion Snow (4) Honglak Lee (4) Daniel Jurafsky (4) Pieter Abbeel (4) Adam Coates (4) Quoc V. Le (4)

Research topics

Core AI (2) Robotics (1)

Keywords

feature learning (12) unsupervised learning (7) unsupervised feature learning (6) representation learning (6) convolutional neural network (5) chest x-ray (5) computer vision (4) image classification (3) sparse coding (3) hierarchical feature (3) hierarchical feature learning (2) deep learning (2) contrastive learning (2) feature representation (2) medical imaging (2) object detection (2) structured prediction (2) reinforcement learning (2) feature extraction (2) hierarchical learning (2)

Papers

Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation MIDL 2024 DataPerf: Benchmarks for Data-Centric AI Development NIPS 2023 MedSelect: Selective Labeling for Medical Image Classification Using Meta-Learning MIDL 2022 MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models MIDL 2021 MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation MLHC 2021 CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays MLHC 2021 Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays MIDL 2021 CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation MIDL 2021 Evaluating the Disentanglement of Deep Generative Models through Manifold Topology ICLR 2021 CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison AAAI 2019 Countdown Regression: Sharp and Calibrated Survival Predictions UAI 2019 End-To-End People Detection in Crowded Scenes CVPR 2016 Parsing with Compositional Vector Grammars ACL 2013 Emergence of Object-Selective Features in Unsupervised Feature Learning NIPS 2012 Deep Learning of Invariant Features via Simulated Fixations in Video NIPS 2012 Convolutional-Recursive Deep Learning for 3D Object Classification NIPS 2012 Large Scale Distributed Deep Networks NIPS 2012 Semantic Compositionality through Recursive Matrix-Vector Spaces CONLL 2012 Semantic Compositionality through Recursive Matrix-Vector Spaces EMNLP 2012 Sparse Filtering NIPS 2011 Selecting Receptive Fields in Deep Networks NIPS 2011 ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning NIPS 2011 Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection NIPS 2011 Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions EMNLP 2011 Learning Word Vectors for Sentiment Analysis ACL 2011 Unsupervised learning models of primary cortical receptive fields and receptive field plasticity NIPS 2011 Energy Disaggregation via Discriminative Sparse Coding NIPS 2010 Tiled convolutional neural networks NIPS 2010 Unsupervised feature learning for audio classification using convolutional deep belief networks NIPS 2009 Measuring Invariances in Deep Networks NIPS 2009 Learning to Merge Word Senses CONLL 2007 Learning to Merge Word Senses EMNLP 2007 Sparse deep belief net model for visual area V2 NIPS 2007 Efficient multiple hyperparameter learning for log-linear models NIPS 2007 Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion NIPS 2007 An Application of Reinforcement Learning to Aerobatic Helicopter Flight NIPS 2006 Semantic Taxonomy Induction from Heterogenous Evidence ACL 2006 Semantic Taxonomy Induction from Heterogenous Evidence COLING 2006 Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation Pipelines EMNLP 2006 Efficient sparse coding algorithms NIPS 2006 Learning Factor Graphs in Polynomial Time and Sample Complexity JMLR 2006 Robotic Grasping of Novel Objects NIPS 2006 Map-Reduce for Machine Learning on Multicore NIPS 2006 Discriminative Training of Kalman Filters RSS 2005 Latent Dirichlet Allocation JMLR 2003